Abstract

It has already been shown that spectral estimation can be improved when applied to subband outputs of an adapted
filterbank rather than to the original fullband signal. In the present paper, this procedure is applied jointly to a novel
predictive autoregressive (AR) model. The model exploits time-shifting and is therefore referred to as time-shift AR (TSAR)
model. Estimators are proposed for the unknown TS-AR parameters and the spectrum of the observed signal. The
TS-AR model yields improved spectrum estimation by taking advantage of the correlation between subseries that arises
after decimation. Simulation results on signals with continuous and line spectra that demonstrate the performance of the
proposed method are provided.

Item Type:

Article

Additional Information:

Thanks to Elsevier editor. The definitive version is available at http://www.sciencedirect.com The original PDF of the article can be found at Signal Processing website : http://www.sciencedirect.com/science/journal/01651684